Method and system for facial recognition

1. A method for face liveness detection, comprising: receiving a first image comprising a face of a user; determining one or more two-dimensional (2D) facial landmark points based on the first image; determining a three-dimensional (3D) pose of the face in the first image based on the one or more 2D facial landmark points and a first set of 3D facial landmark points, wherein the first set comprises one or more 3D facial landmark points in a 3D face model of the face of the user, and the one or more 3D facial landmark points of the first set correspond to the one or more 2D facial landmark points; determining a homography mapping between the one or more 2D facial landmark points and a second set of 3D facial landmark points, wherein the second set comprises one or more other 3D facial landmark points that are perspectively projected from the one or more 3D facial landmark points of the first set based on the 3D pose; and determining liveness of the face in the first image based on the homography mapping to determine actual presence of the user during capture of the first image.

2. The method of claim 1 , further comprising: transforming the one or more 2D facial landmark points to one or more other 2D facial landmark points based on one or more parameters of an image sensor that captured the first image to generate a second image including the one or more other 2D facial landmark points; wherein the homography mapping is further based on the second image.

3. The method of claim 1 , further comprising: receiving a request to register a new user, wherein the request comprises multiple facial images of the new user at different poses; determining and tracking at least one 2D facial landmark point in the multiple facial images; and generating a 3D face model of a face of the new user based on the at least one 2D facial landmark point and one or more parameters of a sensor.

4. The method of claim 1 , further comprising: refining the 3D pose and the homography mapping to reduce a distance between the one or more 2D facial landmark points and the one or more other 3D facial landmark points of the second set.

5. The method of claim 1 , wherein determining liveness of the face in the first image comprises: determining a deviation of the homography mapping from an identity matrix to detect whether the face in the first image is one of a 3D face presented to an image sensor that captured the first image or a 2D facial image of the user presented to the image sensor.

6. The method of claim 1 , wherein determining a homography mapping comprises decomposing the homography mapping based on one or more parameters of an image sensor that captured the first image.

7. The method of claim 1 , further comprising: performing facial verification based on the first image to determine the user is a registered user; and retrieving the 3D face model of the face of the user in response to determining the user is a registered user.

8. A system for face liveness detection, comprising: at least one processor; and a non-transitory processor-readable memory device storing instructions that when executed by the at least one processor causes the at least one processor to perform operations including: receiving a first image comprising a face of a user; determining one or more two-dimensional (2D) facial landmark points based on the first image; determining a three-dimensional (3D) pose of the face in the first image based on the one or more 2D facial landmark points and a first set of 3D facial landmark points, wherein the first set comprises one or more 3D facial landmark points in a 3D face model of the face of the user, and the one or more 3D facial landmark points of the first set correspond to the one or more 2D facial landmark points; determining a homography mapping between the one or more 2D facial landmark points and a second set of 3D facial landmark points, wherein the second set comprises one or more other 3D facial landmark points that are perspectively projected from the one or more 3D facial landmark points of the first set based on the 3D pose; and determining liveness of the face in the first image based on the homography mapping to determine actual presence of the user during capture of the first image.

9. The system of claim 8 , wherein the operations further include: transforming the one or more 2D facial landmark points to one or more other 2D facial landmark points based on one or more parameters of an image sensor that captured the first image to generate a second image including the one or more other 2D facial landmark points; wherein the homography mapping is further based on the second image.

10. The system of claim 8 , wherein the operations further include: receiving a request to register a new user, wherein the request comprises multiple facial images of the new user at different poses; determining and tracking at least one 2D facial landmark point in the multiple facial images; and generating a 3D face model of a face of the new user based on the at least one 2D facial landmark point and one or more parameters of a sensor.

11. The system of claim 8 , wherein the operations further include: refining the 3D pose and the homography mapping to reduce a distance between the one or more 2D facial landmark points and the one or more other 3D facial landmark points of the second set.

12. The system of claim 8 , wherein determining liveness of the face in the first image comprises: determining a deviation of the homography mapping from an identity matrix to detect whether the face in the first image is one of a 3D face presented to an image sensor that captured the first image or a 2D facial image of the user presented to the image sensor.

13. The system of claim 8 , wherein determining a homography mapping comprises decomposing the homography mapping based on one or more parameters of an image sensor that captured the first image.

14. The system of claim 8 , wherein the operations further include: performing facial verification based on the first image to determine the user is a registered user; and retrieving the 3D face model of the face of the user in response to determining the user is a registered user.

15. A non-transitory computer readable storage medium including instructions to perform a method for face liveness detection, the method comprising: receiving a first image comprising a face of a user; determining one or more two-dimensional (2D) facial landmark points based on the first image; determining a three-dimensional (3D) pose of the face in the first image based on the one or more 2D facial landmark points and a first set of 3D facial landmark points, wherein the first set comprises one or more 3D facial landmark points in a 3D face model of the face of the user, and the one or more 3D facial landmark points of the first set correspond to the one or more 2D facial landmark points; determining a homography mapping between the one or more 2D facial landmark points and a second set of 3D facial landmark points, wherein the second set comprises one or more other 3D facial landmark points that are perspectively projected from the one or more 3D facial landmark points of the first set based on the 3D pose; and determining liveness of the face in the first image based on the homography mapping to determine actual presence of the user during capture of the first image.

16. The computer readable storage medium of claim 15 , wherein the method further comprises: transforming the one or more 2D facial landmark points to one or more other 2D facial landmark points based on one or more parameters of an image sensor that captured the first image to generate a second image including the one or more other 2D facial landmark points; wherein the homography mapping is further based on the second image.

17. The computer readable storage medium of claim 15 , wherein the method further comprises: receiving a request to register a new user, wherein the request comprises multiple facial images of the new user at different poses; determining and tracking at least one 2D facial landmark point in the multiple facial images; and generating a 3D face model of a face of the new user based on the at least one 2D facial landmark point and one or more parameters of a sensor.

18. The computer readable storage medium of claim 15 , wherein the method further comprises: refining the 3D pose and the homography mapping to reduce a distance between the one or more 2D facial landmark points and the one or more other 3D facial landmark points of the second set.

19. The computer readable storage medium of claim 15 , wherein determining liveness of the face in the first image comprises: determining a deviation of the homography mapping from an identity matrix to detect whether the face in the first image is one of a 3D face presented to an image sensor that captured the first image or a 2D facial image of the user presented to the image sensor.

20. The computer readable storage medium of claim 15 , wherein determining a homography mapping comprises decomposing the homography mapping based on one or more parameters of an image sensor that captured the first image.